Retailer should emerge products as their consumers are looking for and keep up with what they have to tell and do. Without a great product data, even an incredible product selection does not help shoppers find what they're look foring. In fact, its not only small retailers but also famous retailers struggle to develop optimal data so that shoppers find the right product. Vast majority of retailers recognize the product data improvement is the key to business success and higher revenue.

Below are the most painful issues of under-optimized product data.

1. Inconsistent product attribution.

This pain is seen in every retailer but especially prevalent to sellers who depend on third parties for their product data. Around 71% retailers have missing product data feed. Consequently, relevant products disappear and irrelevant present themselves. 73% of shoppers fear that products are artificially limited and 40% express a distrust in search. Pervasively 75% of websites analyzed to miss accurate product attribution when searching, filtering or navigating.

2. Merchant speech instead of shopper speech

Product data is communicative to shoppers and retailers. This product language becomes irrelavant in case of fueled merchant data reflecting how a retailer thinks about a product but a shopper describes it. To be worse, staying up to date with consumer vocabulary is tough and time consuming.

3. Undermined product content

Product content is the number one factor of purchase decision to 73% of shoppers according to Comscore and UPS recent study. Retailers have made wonderful investment in content development included imagery, video, description, guide, reviews, etc. Unfortunately, these contents are not usable for search or navigaton. Despite retailers are aware of this efficency, their hands tied due to insufficient time and tools to mine and structure proper attributes for search.

4. Uniformed merchant team vs. under-optimized product data

If a retailer's system gives signs on what influences buying decision. The time and effor required to find such insight are not available resulting in missed opportunities for improvement and left revenues. In fact, 79% retailers do not understand how successful filters helps shoppers make a purchase decision.

Easing this pain the sooner the better. Crate and Barrel updates its product data and achieves 128% higher revenues made through filters and facet navigation. Urban Decay incorporates data review in the navigation, resulting in 16% lift in contingent values rights.

Recommendations

There are four quick tips for retailers to improve poor product data.

  • Plan a solid structure to ensure each product tagged consistently
  • Speak customer language
  • Question how shoppers look for products and develop categories and attributes properly
  • Incorporate rich product information into site search and navigation
  • Uncover insights and make necessary changes